A research team led by Huijun Wu and Chang Su constructed what they call the IEC nexus, a unified framework linking industrial structure, ecological environment and carbon emissions into a single analytical system. The approach borrows from the ‘nexus’ thinking first proposed at the 2011 Bonn Conference for water, energy and food, in which interdependent systems mutually reinforce or constrain one another. Rather than treating economic transformation, pollution and greenhouse gases as separate policy files, the team measured all three simultaneously for Huainan between 2000 and 2022, using entropy-weighted indicators drawn from national and provincial statistical yearbooks, energy inventories and local environmental bulletins. Carbon emissions were calculated following IPCC guidelines, converting the physical consumption of coal, oil and natural gas into carbon dioxide using fuel-specific heating values, carbon contents and oxidation rates.

The centerpiece of the analysis is the coupling coordination degree, a metric that ranges from zero to one and captures how well the three subsystems evolve together rather than at each other’s expense. The results tell a story in three acts. In the early period from 2000 to 2008, the industrial subsystem lagged badly behind, with its evaluation index fluctuating between just 0.13 and 0.44 while environmental and carbon indices ran higher. During a difficult transition from 2008 to 2016, the accumulated costs of coal dependence became visible: the coordination degree actually slipped from 0.753 in 2012 to 0.741 in 2016 as environmental quality briefly deteriorated. Then, from 2016 onward, the system entered what the authors describe as a high-quality development stage, with the overall coordination degree climbing from 0.552 in 2000 to 0.832 in 2022, crossing from ‘barely coordinated’ into the ‘good coordinated development’ band.

Perhaps the most striking finding is how lopsided the progress has been. The industrial structure index surged to about 0.52 by 2020 and the ecological environment index climbed to roughly 0.94, yet the carbon emissions index crawled along at only about 0.40. In other words, Huainan has learned to restructure its economy and clean its air far faster than it has learned to decarbonize. The coupling degree itself remained stubbornly high throughout, ranging from 0.754 to 0.991, which the researchers interpret as evidence that the three subsystems are locked into tight mutual dependence: improvements in one cannot be sustained for long without corresponding movement in the others.

To identify what was actually holding the city back, the team applied an obstacle degree model that decomposes the coordination deficit into individual indicators. The verdict shifted dramatically over the two decades studied. In 2000, the industrial structure subsystem accounted for a dominant 71.04 percent of the total obstacle, driven largely by weak tertiary-sector employment and stagnant rural incomes. By 2022 that share had fallen to 45.07 percent, while the ecological environment subsystem more than doubled its contribution from 15.03 percent to 37.48 percent, and carbon emissions rose from 13.93 percent to 17.46 percent. The bottleneck has migrated: as structural constraints eased, pollution intensity, particularly sulfur dioxide emissions per unit of GDP, and the lingering weight of coal-linked industry became the new front line.

The study then turned from diagnosis to prophecy, pairing the STIRPAT model, a regression framework relating environmental pressure to population, affluence and technology, with a Grey GM(1,1) forecasting model. Because the six explanatory variables, including population, per capita GDP, urbanization, secondary-industry share, energy intensity and energy structure, showed substantial multicollinearity, the team calibrated the model with ridge regression, setting the ridge parameter at 0.14 and achieving an R-squared of 0.868 with an average fitting error of 6.18 percent. The authors are careful to note that only the population coefficient reached even marginal statistical significance, so the projections should be read as conditional scenarios rather than firm causal predictions.

Those scenarios, however, are revealing. Under a business-as-usual pathway, Huainan’s carbon emissions would not peak until around 2035, five years past the national target, at roughly 29.6 million tons, about 1.27 times the 2020 level. Merely optimizing industrial structure barely improves that timing. The low-carbon and energy-saving scenario, which combines faster cuts in energy intensity with a cleaner energy mix, brings the peak forward to 2030 at about 28.7 million tons while preserving steady economic growth, making it the pathway the authors judge most realistic and aligned with China’s dual carbon goals. An aggressive green development scenario peaks earliest, in 2028 at just 24.9 million tons, but only by deliberately throttling population growth and urbanization. At the other extreme, an extensive development scenario that prioritizes raw economic expansion delays the peak to 2040 at a hefty 35.1 million tons.

The Grey model projections for the coordination degree itself add a further layer of nuance. Across all scenarios the index continues rising through 2036, but the green development pathway approaches perfect coordination by 2032, followed by industrial structure optimization, then the low-carbon energy pathway, with the extensive scenario trailing the field. The ordering suggests that structural adjustment delivers the quickest coordination gains, while energy-focused measures, though slower to register, are what actually bend the emissions curve. For a city where coal mining has caused land subsidence, water pollution and ecosystem degradation across some of eastern China’s most representative subsidence zones, both fronts matter.

The policy implications the authors draw are refreshingly specific. Huainan should not simply shrink its secondary sector, they argue, but upgrade its internal composition, cultivating new energy equipment manufacturing, photovoltaic and wind industries, digital economy sectors and modern logistics, while converting mining subsidence zones into wetland parks and ecological conservation areas. Coal-power plants should pursue ultra-low emission retrofits and carbon capture technologies, and the city should build a dynamic monitoring system around the very indicators the obstacle analysis flagged: tertiary employment, pollution intensity, energy intensity and energy structure. Because the constraints themselves shift over time, the authors contend, governance must be adaptive and coordinated across industrial, environmental, energy and planning departments rather than siloed.

The study is candid about its limits. A 2016 administrative boundary change, when Shou County was incorporated into Huainan, complicates comparisons of population-related indicators across the time series, and some missing data were filled by regression-based imputation. The findings from a single coal city may not transfer cleanly to regions with different resource endowments, and the forecasting models rest on assumptions about parameter stability that real-world shocks could upend. The authors also stress that their correlations describe temporal associations, not proven causal effects. Even so, the broader message travels well beyond Anhui: for the hundreds of resource-dependent cities worldwide staring down decarbonization deadlines, Huainan’s two-decade ledger suggests that industrial restructuring, ecological restoration and carbon mitigation can indeed rise together, but only if energy intensity and energy structure are treated as the decisive battleground rather than an afterthought.

Subject of Research: Coupling coordination of industrial structure, ecological environment and carbon emissions in the coal-resource city of Huainan, China

Article Title: Can coal-resource cities achieve high-quality coordination of industry, environment, and carbon? Evidence from Huainan, China

Article References: Wu, H., Su, C., Zhang, Y., Li, M., Kong, X., Liu, Y., & Gao, L. (2026). Can coal-resource cities achieve high-quality coordination of industry, environment, and carbon? Evidence from Huainan, China. Environmental and Sustainability Indicators, 32, Article 101541. https://doi.org/10.1016/j.indic.2026.101541

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101541

Keywords: Huainan, coal-resource cities, carbon emissions, coupling coordination degree, STIRPAT model, energy transition, industrial structure, ecological environment, carbon peak, obstacle degree analysis, China dual carbon goals, GM(1,1) forecasting

The research, published in Environmental and Sustainability Indicators, was conducted by Herfita Rizki Hasanah Gurning of IPB University and colleagues, who set out to answer a question that has largely been overlooked in previous work: do provinces with strong marine economies also possess the economic, social and environmental capacities needed to sustain them, and are comparatively developed provinces actually making full use of their marine potential? Earlier studies had tended to treat regional development simply as economic growth or environmental carrying capacity, rather than as a distinct, multidimensional system in its own right.

To build a comparable sample, the team first used K-medoids clustering on data from 34 Indonesian provinces covering 2019 to 2023, drawing on indicators of marine and brackishwater fisheries intensity, marine transport intensity, marine tourism intensity and the share of coastal villages. The two-cluster solution proved statistically strongest, with the highest Silhouette Coefficient of 0.448 and the lowest Davies-Bouldin Index of 0.761, and it kept a balanced minimum cluster size of 14 provinces. Twenty provinces emerged with comparatively high marine economic intensity, and these formed the analytical sample. Notably, the researchers measured marine subsector contributions against non-mining gross regional domestic product, a deliberate choice to avoid distorting results in provinces where extractive industries dominate headline output figures.

The study then applied Grey Relational Analysis, a technique well suited to settings where comprehensive provincial marine data are scarce, to construct a Marine Economy Performance Index and a Regional Development Performance Index for each province in 2019 and 2023. The marine economy index captured economic scale, economic structure and economic efficiency, while the regional development index combined economic indicators such as non-mining growth and unemployment, social indicators including poverty, the Human Development Index and the Gini ratio, and environmental measures comprising a composite environmental quality index and a disaster risk index from Indonesia’s National Disaster Management Authority.

The results reveal a striking divergence between the two systems. Average marine economic performance barely moved, slipping from 0.55 in 2019 to 0.54 in 2023, while average regional development performance rose from 0.56 to 0.62. Within the marine economy, the structure dimension improved markedly, from 0.60 to 0.65, reflecting diversification away from primary fisheries dependence and stronger marine tourism, but the efficiency dimension fell from 0.53 to 0.44 as capture fisheries and aquaculture productivity weakened across many provinces. Bali made the most dramatic climb, rising from twelfth to second place in marine economic performance as its structure score reached a perfect 1.00, while North Maluku held first place with its efficiency dimension hitting the ideal value. At the other extreme, DKI Jakarta plummeted from sixth to twentieth as its productivity scores collapsed.

Regional development told a different story. Bali rose from third to first place with an index of 0.77, Riau Islands held second, and West Nusa Tenggara and North Sulawesi posted some of the largest gains. The economic dimension improved most, from 0.59 to 0.67, and the environmental dimension rose from 0.54 to 0.61, but the social dimension advanced only modestly, from 0.54 to 0.58. That slower social progress matters, the authors argue, because economic and environmental gains in coastal regions do not automatically translate into improvements in welfare, inclusion or human development, and unequal benefit distribution remains a persistent challenge in marine-dependent communities.

The core of the analysis lies in the coupling coordination degree, a measure that combines the proportional balance between the two indices with their overall development level. Average coordination improved only slightly, from 0.74 in 2019 to 0.76 in 2023, leaving most provinces in the intermediate coupling range of 0.7 to 0.8. No province reached the high-quality coupling category, defined as 0.9 or above. Bali and North Maluku entered the good coupling range, at 0.85, after improving both subsystems simultaneously, while Aceh moved up from primary to intermediate coupling. By contrast, North Kalimantan slipped from good to intermediate coordination, and DKI Jakarta showed the sharpest imbalance, with regional development improving even as marine economic performance declined sharply. No province recorded the reverse pattern of rising marine performance alongside falling regional development.

To pinpoint what was holding coordination back, the team deployed an Obstacle Degree Model using entropy weights, which quantifies how far each indicator sits from its ideal state and how much it constrains the system overall. The findings were unambiguous. The marine economy subsystem accounted for 65.43 percent of the total obstacle degree in 2019, rising to 68.25 percent in 2023. Within it, the productivity of marine and brackishwater aquaculture was the single largest obstacle, growing from 28.93 percent to 30.27 percent, followed by the contribution of marine transportation to regional output, which climbed from 14.66 percent to 17.34 percent. Together these two indicators accounted for nearly half of all constraints by 2023, and their dominance intensified over the study period.

The provincial heatmaps add important nuance. Aquaculture productivity was especially problematic in North Kalimantan and the Riau Islands, where its obstacle degree exceeded 40 percent, while marine transportation was the dominant constraint in Bali despite the island’s overall gains. In North Maluku, disaster risk emerged as the leading obstacle in 2023, showing that even provinces with strong coordination can carry acute vulnerabilities in a single dimension. Prior research suggests aquaculture performance is often limited by capital constraints, high feed costs, disease outbreaks, declining water quality and unreliable electricity, while Indonesia’s maritime transport challenges include limited port capacity, weak intermodal connectivity and insufficient institutional coordination, though the study itself is diagnostic rather than causal and does not identify which mechanisms operate in each province.

The policy implications are concrete. The authors argue that provincial governments should prioritize aquaculture productivity through better production technology, water-quality and disease management, infrastructure, and access to capital; strengthen the economic role of marine transportation through port capacity, logistics and intermodal connectivity; and embed disaster-risk reduction more systematically into coastal planning. Just as importantly, because the obstacle structure differs from province to province, a uniform national approach is unlikely to work. Provinces where both systems improved need policies that consolidate gains, while those with stagnant or declining marine performance need targeted interventions. As Indonesia pushes its blue economy agenda across a fragmented archipelago, the study suggests that converting marine potential into broad-based regional benefit depends less on expanding production than on fixing the specific, measurable bottlenecks — above all pond productivity and maritime connectivity — that keep the sea and the shore from developing together.

Subject of Research: Coupling coordination between marine economy performance and regional development across coastal Indonesian provinces

Article Title: Coupling coordination and obstacle analysis of the marine economy and regional development: Evidence from coastal Indonesia

Article References: Gurning, H. R. H., Fauzi, A., Rustiadi, E., & Pravitasari, A. E. (2026). Coupling coordination and obstacle analysis of the marine economy and regional development: Evidence from coastal Indonesia. Environmental and Sustainability Indicators, 32, Article 101513. https://doi.org/10.1016/j.indic.2026.101513

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101513

Keywords: Indonesia, marine economy, regional development, aquaculture productivity, coupling coordination degree, marine transportation, coastal provinces, blue economy, Grey Relational Analysis, obstacle degree model, disaster risk, sustainable development